Before wetry to solve the predictor puzzle havingpredictions for the six major indices on threetime frames plus the Omega predictions for the NASDAQ / NASDAQ100 and the S&P500, wemake some general considerations.

Index Value Calculations:

The index value calculations usea so-called CAP – weightedprocess, which means, thatthe company which have a biggercapitalization, willhave a bigger impactwithin the index. But just because of the huge cap differences even within the NASDAQ100, the NASDAQ / NASDAQ100 uses a so-called modified cap weightedcalculation mechanism, which assures, thatthe bigger capitalization companies have bigger impact, but their impact is not 10 times bigger, if their capitalizaton is 10 times bigger than the other index component. This way theorder of importance within the index is maintained, reserved and determined by the cap size.(Note that the DOW index is aprice-weighted index.)

Index Size:

The biggest index by far is the S&P500 index, than the NASDAQ index, thanthe S&P100 index. Smaller is the NASDAQ100. Much smaller indices are the S&P400 (Mid Cap) and S&P600 (Small Cap) indices.

Index components and interrelationships:

Note that some companies mightbe member of multiple indices. For example Intel (INTC is a NASDAQ company, but also member of the S&P500the NASDAQ100 and the S&P100 indices.)Thismeansthat we can see / calculate correlations between indices.

During early 2010, the followingoverlapping were present in the indices:

71 NASDAQ100 companies are also member of the S&P500list of companies(These amounts to 14.2%of the companies in the S&P500.

100 or 100% of the S&P100 index components are also member of the S&P500 index (These amounts to 20% of the S&P500 companies.)

93NASDAQ companies are also member of the S&P500 index. (These amounts to 18.6% of the companies in the S&P500 index.)

14 or 14% ofthe NASDAQ100 companies are member of the S&P100 index. This also shows that technology is a relatively small, though importantpart of the US economy and the indices reflecting the whole US economy.

Obviously None of the S&P400 (Mid Cap) companies are member ofany other major index we calculate.

None of the S&P600 companies are member of any other index we calculate.

So if a huge tech companymake a big price move, than the Biggest impact is in the NASDAQ100 index, abit smaller within the NASDAQ index,andagain smaller the impact in the S&P100 and S&P500 indices, assuming that themove in the given stock isnotmoving much the other index components, it is an isolated move.

Conversely if a big S&P100 componet make a big price move, usually the impact on the index itself is smaller, as the S&P100 and S&P500 index is more diversified than the NASDAQ/ NASDAQ100 indices.

Note that these numbers arechangingevery year, as indices get modified, if a company get out of theindexfor some reason and a new company get in.

Analyzing the prediction data:

We would like to note here that the marketisconstantly impacted by the cumulative effects of many different cycles (4 Days cycle, 4 weeks cycle 4 years cycle...) andtheimpacts of that is, that the market changes direction,but not necessarily at the beginning of the week or at the beginning of the month, so those direction changesusually occur in betweenof those prediction periods.

When we selected the Index and theasset class to playwe check first the Daily predicted direction for that index, and the win probability of that prediction.

For example we play the NASDAQ index, and theprediction is Bullish, with 77 % Win probability.

That is a nice win probability, as it is a bit above average, but that alone is still not enough to make the decision to open a position toholdovernight.

So we would like to collectmore confirmation. We check, if the other major indices alsopredicted to move in the same direction. Ifboth the NASDAQ and the S&P indices predicted to move in the same direction, thanthat information mean two things.The win probability is a bit increased (by 1.6% - 3.8%)and that the market more probably makes a bigger move and not hesitate and stay in a small range or struggle to move, ifthe predicted direction ofthe major indices shows some divergences.

Second we check the weekly prediction. Here we consider three things.

-The predicted weekly direction.

-The predicted weekly win probability.

-The time / dateor how old is that weekly prediction is.

Ifthe win probability is about average for the week (Say 78% for the NASDAQ) than it does not add much to the picture, but if the win probability is much bigger, than the average, say 85 – 93%, thanit increasesthe win probability of our overnight position, especiallyif the prediction is freshly calculated (We calculate that on Friday for the next week, assuming that Friday is a market day.)

If we are already in the second half of the week (Wednesday evening or Thursday evening)than the weekly prediction have minimum impact.

Weekly prediction data mightincrease / decrease win probability by 2-6% depending on the status of the above three points. (The biggest support being a fresh Weely prediction with high win probabilitypointing in the same direction asthe Daily prediction.)

Third we checkthe monthly prediction. We acknowledge, thatthis data have minimal impact on the decision for overnight position,evenat the beginning of the month, when this prediction is relatively fresh. It has less, than 2% impact on the final win probability. It might have a role for the position size selection.

What we consider next andreally important is the Omega prediction.

Omega prediction have major impact on our decision, because of many reasons.As we mentioned, it has relatively low correlation with the other daily predictions, andfails rarely at the same time, whenthe Daily prediction fails. We also stated,thatthe Daily predictionis better to predict the market movement at the beginningof the prediction period (For Daily predictionnamelyfor the first 30 – 90 minutes.) whereas the Omega prediction is better to predict the market movement for the second half of the day.

The Daily predictions havelittle capability to predict thedirection of the Gap, (GAP prediction capability is roughly 52%) but the Omegapredictionhas a much better capability to predict the GAP direction. (It was about 65%during the past 6 month tillNov 2010.)

During the previous6 month period, the average Win probability of the Omega prediction for the NASDAQ was 72%.If we require, that the Omega predictionAND the Daily prediction must point in the same direction to open overnight position, than the statistics will changenotably.

During the same period theWin probability for Long positions was78.2% and the win probability for short positions was87.23%On average the win probability,ifboth the Daily prediction and the Omega prediction pointedto the same direction was82.79%This means, thatwe increased the Win probabilityby about 10% from 72 to 82.79, just by adding one condition to the equation.

The other impact of this was,that we had much lessoccasion, (Less number of trades) when this requirement fulfilled. It happened54% of the days / cases.

I would even say, that the impact of the Omega prediction isbigger then the impact of the daily prediction, havingaverage Daily prediction win probability.If we haveGAPPY markets, when the overnight risk is increased, thanthe Omega prediction play even bigger role.

We do not have defined6 different states for the Omega prediction, as we did for the Daily prediction.

Ifthe Omega prediction is Bearish and the Daily prediction is Bullish, than we do not open overnight position.If the Omega prediction is Bearish to Neutral, and the Daily prediction is Bullish, thanat least we do not have clear argument, against opening a Long position.So if „Neutral”mentioned for Omega prediction, than the Daily prediction direction mightbe played, even ifthe two prediction not completely agree.

If we play the NASDAQ / NASDAQ100,then thepredicted direction for the S&P400 and S&P600has also minimalrelevance.Smalland mid cap companiesplay a role in the breath – type indicators, buthave little direct impact on the bigger indices.Theimpact direction is usually the reverse, so that themajors might pull them up / downeven more than they move.

The impact of a 5% prediction win probability difference could be very high for our yearlytrading result. Let’s see that in the following example:

Assume we trade the overnight prediction data 100 times a year or about 40% of the total yearly trading days. Since we are taking the risk of the overnight GAP, the Average Win size isclose to the average loss size.If we have a 75% win probability, playing with a 100 K account and the average win and the average loss is also 1K, than our yearly profit is75K – 25K = 50 K $ (Not calculating with the reinvestment of the gain.)

If we manage to increase the Win probability by 5% to 80%, than the total win will be 80K, the total loss will be 20K, so theresult is 80 – 20 = 60K, which isa 20% better result. (If we are calculating with the reinvestment of the periodic gains than the difference is even bigger.)

Note however, thatthe overnight risk is something we need to take very seriously. The overnight GAPin any index could be 2% or even higher.

(During the past 6 month for example till the beginning of November 2010 we could have 6 big GAP-s against our position, If we opened overnight position at a time, when both the Daily and the Omega prediction pointed in the same direction. The biggest GAPagainst our position was2%, the other big GAPs against our position were between 0.9 – 1.6%) During the past half year the market volatility was about average. (GAPs calculated as:(Today’s Open – Previous day’s Close ) / Previous day’s close * 100 [%])

In the coming articles of this seriesI will write about the relevant technical analysis, and other aspectsthat can further aid us todecreasethe risk and increasethe success ratio of ourstrategy to play overnight position.